EDA Notebook
Sho
11/21/2021
Loading In Data
data <- read.csv("MH_survey_only_higher_index.csv",
na.strings = "NA")
names(data)## [1] "gender" "age_group" "country_lockdown"
## [4] "marital" "smoking" "fivfruitveg"
## [7] "hour_sleep" "shielded" "week_soc_distancing"
## [10] "lockdown_bubble" "athlete" "AIMS_TOTAL"
## [13] "MHC_SF_OVERALL" "HADS_OVERALL" "RES_TOTAL"
## [16] "LONE_TOTAL"data <- data[, -c(17:22)]
# Assigning factors
data$gender <- factor(data$gender)
data$age_group <- factor(data$age_group)
data$country_lockdown <- factor(data$country_lockdown)
data$marital <- factor(data$marital)
data$smoking <- factor(data$smoking)
data$fivfruitveg <- factor(data$fivfruitveg)
data$shielded <- factor(data$shielded)
data$week_soc_distancing <- factor(data$week_soc_distancing)
data$athlete <- factor(data$athlete)Pairs Plot
plot(MHC_SF_OVERALL ~ gender, data = data)
plot(MHC_SF_OVERALL ~ age_group, data = data)
plot(MHC_SF_OVERALL ~ country_lockdown, data = data)
plot(MHC_SF_OVERALL ~ marital, data = data)
plot(MHC_SF_OVERALL ~ smoking, data = data)
plot(MHC_SF_OVERALL ~ fivfruitveg, data = data)
plot(MHC_SF_OVERALL ~ hour_sleep, data = data)
plot(MHC_SF_OVERALL ~ week_soc_distancing, data = data)
plot(MHC_SF_OVERALL ~ shielded, data = data)
plot(MHC_SF_OVERALL ~ lockdown_bubble, data = data)
plot(MHC_SF_OVERALL ~ athlete, data = data)
plot(MHC_SF_OVERALL ~ jitter(AIMS_TOTAL), data = data)
abline(line(data$AIMS_TOTAL, data$MHC_SF_OVERALL))
plot(MHC_SF_OVERALL ~ HADS_OVERALL, data = data)
plot(MHC_SF_OVERALL ~ RES_TOTAL, data = data)
plot(MHC_SF_OVERALL ~ LONE_TOTAL, data = data)
plot(MHC_SF_OVERALL ~ lockdown_bubble, data = data)
data %>% select(gender, athlete) %>% table()## athlete
## gender 1 2
## 1 201 152
## 2 162 238data %>% select(age_group, athlete) %>% table()## athlete
## age_group 1 2
## 1 59 14
## 2 127 76
## 3 86 96
## 4 61 98
## 5 21 52
## 6 7 41
## 7 2 13data %>% select(shielded, athlete) %>% table()## athlete
## shielded 1 2
## 1 28 38
## 2 335 352data %>% select(marital, athlete) %>% table()## athlete
## marital 1 2
## 1 177 100
## 2 164 263
## 3 4 5
## 4 16 14
## 5 2 8data %>% select(fivfruitveg, athlete) %>% table()## athlete
## fivfruitveg 1 2
## 1 201 209
## 2 162 181data %>% select(smoking, athlete) %>% table()## athlete
## smoking 1 2
## 1 268 258
## 2 30 39
## 3 28 56
## 4 31 15
## 5 4 17
## 6 2 3
## 7 0 2data %>% ggplot(aes(x=gender, y=MHC_SF_OVERALL, color=athlete)) + geom_boxplot()## Warning: Removed 65 rows containing non-finite values (stat_boxplot).
Step-wise Regression
model_full <- lm(MHC_SF_OVERALL ~ ., data = data)
summary(model_full)##
## Call:
## lm(formula = MHC_SF_OVERALL ~ ., data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -25.026 -5.583 0.000 5.827 30.969
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 50.246527 6.907029 7.275 0.0000000000017282 ***
## gender2 2.711660 0.972984 2.787 0.00556 **
## age_group2 1.318527 1.555409 0.848 0.39709
## age_group3 1.873309 1.878811 0.997 0.31931
## age_group4 3.877951 2.031917 1.909 0.05701 .
## age_group5 2.273929 2.364697 0.962 0.33680
## age_group6 9.094306 3.214220 2.829 0.00489 **
## age_group7 1.722124 5.298284 0.325 0.74532
## country_lockdown2 1.487663 1.000024 1.488 0.13760
## country_lockdown3 1.199211 9.400229 0.128 0.89855
## country_lockdown4 1.009035 6.667576 0.151 0.87978
## country_lockdown5 1.751674 9.313891 0.188 0.85091
## country_lockdown7 -2.933821 11.393542 -0.257 0.79692
## marital2 0.154912 1.301414 0.119 0.90531
## marital3 -3.141366 5.470277 -0.574 0.56610
## marital4 1.669728 2.488518 0.671 0.50261
## marital5 6.093416 6.541366 0.932 0.35212
## smoking2 1.043609 1.505094 0.693 0.48845
## smoking3 -0.776139 1.585909 -0.489 0.62482
## smoking4 2.121207 1.792722 1.183 0.23739
## smoking5 2.863919 3.375812 0.848 0.39672
## smoking6 -2.292072 4.220523 -0.543 0.58737
## smoking7 5.377471 7.022743 0.766 0.44427
## fivfruitveg2 -1.081264 0.905453 -1.194 0.23309
## hour_sleep -0.039662 0.457278 -0.087 0.93092
## shielded2 -1.011218 1.579634 -0.640 0.52242
## week_soc_distancing1 -6.783485 7.465507 -0.909 0.36406
## week_soc_distancing2 4.152675 4.204185 0.988 0.32385
## week_soc_distancing3 -0.520379 3.848897 -0.135 0.89252
## week_soc_distancing4 0.721741 3.587953 0.201 0.84067
## week_soc_distancing5 -1.234746 3.546390 -0.348 0.72789
## week_soc_distancing6 -0.336337 3.673477 -0.092 0.92709
## week_soc_distancing7 3.166418 3.717677 0.852 0.39486
## lockdown_bubble 0.014524 0.329413 0.044 0.96485
## athlete2 -2.557496 1.210811 -2.112 0.03526 *
## AIMS_TOTAL -0.005222 0.440542 -0.012 0.99055
## HADS_OVERALL -0.736696 0.091781 -8.027 0.0000000000000102 ***
## RES_TOTAL 0.353353 0.114085 3.097 0.00208 **
## LONE_TOTAL -2.388482 0.320363 -7.456 0.0000000000005206 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.069 on 418 degrees of freedom
## (296 observations deleted due to missingness)
## Multiple R-squared: 0.5949, Adjusted R-squared: 0.558
## F-statistic: 16.15 on 38 and 418 DF, p-value: < 2.2e-16try(step(model_full, direction = "backward"))## Start: AIC=2052.46
## MHC_SF_OVERALL ~ gender + age_group + country_lockdown + marital +
## smoking + fivfruitveg + hour_sleep + shielded + week_soc_distancing +
## lockdown_bubble + athlete + AIMS_TOTAL + HADS_OVERALL + RES_TOTAL +
## LONE_TOTAL
##
## Df Sum of Sq RSS AIC
## - smoking 6 296.1 34674 2044.4
## - country_lockdown 5 189.9 34568 2045.0
## - marital 4 143.6 34522 2046.4
## - AIMS_TOTAL 1 0.0 34378 2050.5
## - lockdown_bubble 1 0.2 34378 2050.5
## - hour_sleep 1 0.6 34379 2050.5
## - shielded 1 33.7 34412 2050.9
## - age_group 6 840.7 35219 2051.5
## - fivfruitveg 1 117.3 34495 2052.0
## <none> 34378 2052.5
## - week_soc_distancing 7 1080.2 35458 2052.6
## - athlete 1 366.9 34745 2055.3
## - gender 1 638.8 35017 2058.9
## - RES_TOTAL 1 789.0 35167 2060.8
## - LONE_TOTAL 1 4571.5 38950 2107.5
## - HADS_OVERALL 1 5298.8 39677 2116.0
##
## Step: AIC=2044.38
## MHC_SF_OVERALL ~ gender + age_group + country_lockdown + marital +
## fivfruitveg + hour_sleep + shielded + week_soc_distancing +
## lockdown_bubble + athlete + AIMS_TOTAL + HADS_OVERALL + RES_TOTAL +
## LONE_TOTAL
##
## Df Sum of Sq RSS AIC
## - country_lockdown 5 248.4 34922 2037.6
## - marital 4 147.8 34822 2038.3
## - hour_sleep 1 0.2 34674 2042.4
## - lockdown_bubble 1 0.2 34674 2042.4
## - AIMS_TOTAL 1 7.4 34681 2042.5
## - age_group 6 787.2 35461 2042.6
## - shielded 1 33.4 34707 2042.8
## - fivfruitveg 1 94.1 34768 2043.6
## <none> 34674 2044.4
## - week_soc_distancing 7 1245.4 35919 2046.5
## - athlete 1 351.5 35026 2047.0
## - gender 1 588.6 35263 2050.1
## - RES_TOTAL 1 787.9 35462 2052.7
## - LONE_TOTAL 1 4700.8 39375 2100.5
## - HADS_OVERALL 1 5384.2 40058 2108.3
##
## Step: AIC=2037.64
## MHC_SF_OVERALL ~ gender + age_group + marital + fivfruitveg +
## hour_sleep + shielded + week_soc_distancing + lockdown_bubble +
## athlete + AIMS_TOTAL + HADS_OVERALL + RES_TOTAL + LONE_TOTAL
##
## Df Sum of Sq RSS AIC
## - marital 4 135.8 35058 2031.4
## - age_group 6 709.9 35632 2034.8
## - hour_sleep 1 0.1 34922 2035.6
## - lockdown_bubble 1 0.3 34923 2035.7
## - AIMS_TOTAL 1 4.7 34927 2035.7
## - shielded 1 40.3 34963 2036.2
## - fivfruitveg 1 114.4 35037 2037.1
## <none> 34922 2037.6
## - week_soc_distancing 7 1312.0 36234 2040.5
## - athlete 1 388.9 35311 2040.7
## - gender 1 721.9 35644 2045.0
## - RES_TOTAL 1 824.8 35747 2046.3
## - LONE_TOTAL 1 4657.7 39580 2092.9
## - HADS_OVERALL 1 5427.3 40350 2101.7
##
## Step: AIC=2031.42
## MHC_SF_OVERALL ~ gender + age_group + fivfruitveg + hour_sleep +
## shielded + week_soc_distancing + lockdown_bubble + athlete +
## AIMS_TOTAL + HADS_OVERALL + RES_TOTAL + LONE_TOTAL
##
## Df Sum of Sq RSS AIC
## - lockdown_bubble 1 0.4 35059 2029.4
## - hour_sleep 1 0.6 35059 2029.4
## - AIMS_TOTAL 1 5.5 35064 2029.5
## - shielded 1 32.3 35090 2029.8
## - fivfruitveg 1 115.5 35174 2030.9
## <none> 35058 2031.4
## - age_group 6 970.4 36029 2031.9
## - week_soc_distancing 7 1340.3 36398 2034.6
## - athlete 1 428.3 35487 2035.0
## - gender 1 719.0 35777 2038.7
## - RES_TOTAL 1 821.1 35879 2040.0
## - LONE_TOTAL 1 4813.9 39872 2088.2
## - HADS_OVERALL 1 5543.8 40602 2096.5
##
## Step: AIC=2029.42
## MHC_SF_OVERALL ~ gender + age_group + fivfruitveg + hour_sleep +
## shielded + week_soc_distancing + athlete + AIMS_TOTAL + HADS_OVERALL +
## RES_TOTAL + LONE_TOTAL
##
## Df Sum of Sq RSS AIC
## - hour_sleep 1 0.7 35059 2027.4
## - AIMS_TOTAL 1 5.6 35064 2027.5
## - shielded 1 32.1 35091 2027.8
## - fivfruitveg 1 115.1 35174 2028.9
## <none> 35059 2029.4
## - age_group 6 1000.9 36059 2030.3
## - week_soc_distancing 7 1340.8 36399 2032.6
## - athlete 1 430.8 35489 2033.0
## - gender 1 725.8 35784 2036.8
## - RES_TOTAL 1 820.8 35879 2038.0
## - LONE_TOTAL 1 4814.4 39873 2086.2
## - HADS_OVERALL 1 5550.2 40609 2094.6
##
## Step: AIC=2027.43
## MHC_SF_OVERALL ~ gender + age_group + fivfruitveg + shielded +
## week_soc_distancing + athlete + AIMS_TOTAL + HADS_OVERALL +
## RES_TOTAL + LONE_TOTAL
##
## Df Sum of Sq RSS AIC
## - AIMS_TOTAL 1 5.7 35065 2025.5
## - shielded 1 31.8 35091 2025.8
## - fivfruitveg 1 114.6 35174 2026.9
## <none> 35059 2027.4
## - age_group 6 1036.8 36096 2028.8
## - week_soc_distancing 7 1340.9 36400 2030.6
## - athlete 1 430.3 35490 2031.0
## - gender 1 730.9 35790 2034.9
## - RES_TOTAL 1 820.4 35880 2036.0
## - LONE_TOTAL 1 4816.0 39875 2084.2
## - HADS_OVERALL 1 5728.0 40787 2094.6
## Error in step(model_full, direction = "backward") :
## number of rows in use has changed: remove missing values?model_step <- lm(MHC_SF_OVERALL ~ gender + age_group + country_lockdown + marital +
smoking + fivfruitveg + shielded + week_soc_distancing +
athlete + AIMS_TOTAL + HADS_OVERALL + RES_TOTAL + LONE_TOTAL, data = data)
summary(model_step)##
## Call:
## lm(formula = MHC_SF_OVERALL ~ gender + age_group + country_lockdown +
## marital + smoking + fivfruitveg + shielded + week_soc_distancing +
## athlete + AIMS_TOTAL + HADS_OVERALL + RES_TOTAL + LONE_TOTAL,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -25.009 -5.583 0.000 5.817 30.939
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 50.016356 5.688292 8.793 < 2e-16 ***
## gender2 2.698905 0.961510 2.807 0.00523 **
## age_group2 1.312310 1.510305 0.869 0.38540
## age_group3 1.872792 1.810821 1.034 0.30163
## age_group4 3.896371 1.988191 1.960 0.05069 .
## age_group5 2.285144 2.299248 0.994 0.32086
## age_group6 9.092557 3.121759 2.913 0.00378 **
## age_group7 1.713001 5.252321 0.326 0.74448
## country_lockdown2 1.490543 0.995118 1.498 0.13492
## country_lockdown3 1.143339 9.358446 0.122 0.90282
## country_lockdown4 1.022004 6.633506 0.154 0.87763
## country_lockdown5 1.744008 9.280041 0.188 0.85102
## country_lockdown7 -2.958809 11.362887 -0.260 0.79469
## marital2 0.148478 1.296610 0.115 0.90889
## marital3 -3.161891 5.451022 -0.580 0.56219
## marital4 1.650123 2.457043 0.672 0.50221
## marital5 6.109372 6.521356 0.937 0.34939
## smoking2 1.044705 1.500482 0.696 0.48666
## smoking3 -0.756128 1.568443 -0.482 0.62999
## smoking4 2.125730 1.786341 1.190 0.23472
## smoking5 2.857888 3.361529 0.850 0.39571
## smoking6 -2.265178 4.199286 -0.539 0.58988
## smoking7 5.411170 6.973880 0.776 0.43823
## fivfruitveg2 -1.079606 0.901978 -1.197 0.23201
## shielded2 -1.007234 1.572714 -0.640 0.52223
## week_soc_distancing1 -6.759509 7.440283 -0.909 0.36413
## week_soc_distancing2 4.124415 4.183626 0.986 0.32478
## week_soc_distancing3 -0.543552 3.824769 -0.142 0.88706
## week_soc_distancing4 0.697073 3.565214 0.196 0.84508
## week_soc_distancing5 -1.260876 3.523748 -0.358 0.72066
## week_soc_distancing6 -0.363132 3.646840 -0.100 0.92073
## week_soc_distancing7 3.149372 3.702261 0.851 0.39544
## athlete2 -2.548032 1.203760 -2.117 0.03487 *
## AIMS_TOTAL -0.005515 0.439135 -0.013 0.98999
## HADS_OVERALL -0.735208 0.090060 -8.164 3.83e-15 ***
## RES_TOTAL 0.353195 0.113777 3.104 0.00204 **
## LONE_TOTAL -2.387924 0.319337 -7.478 4.45e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.047 on 420 degrees of freedom
## (296 observations deleted due to missingness)
## Multiple R-squared: 0.5948, Adjusted R-squared: 0.5601
## F-statistic: 17.13 on 36 and 420 DF, p-value: < 2.2e-16par(mfrow = c(2, 2))
plot(model_step)## Warning: not plotting observations with leverage one:
## 332, 420
## Warning: not plotting observations with leverage one:
## 332, 420## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
model_step2 <- lm(MHC_SF_OVERALL ~ gender + age_group + marital +
smoking + fivfruitveg + shielded + week_soc_distancing +
athlete + AIMS_TOTAL + HADS_OVERALL + RES_TOTAL + LONE_TOTAL, data = data)
summary(model_step2)##
## Call:
## lm(formula = MHC_SF_OVERALL ~ gender + age_group + marital +
## smoking + fivfruitveg + shielded + week_soc_distancing +
## athlete + AIMS_TOTAL + HADS_OVERALL + RES_TOTAL + LONE_TOTAL,
## data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -23.734 -5.345 0.145 5.742 32.263
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 50.19852 5.65581 8.876 < 2e-16 ***
## gender2 2.89320 0.94168 3.072 0.00226 **
## age_group2 1.18059 1.49875 0.788 0.43130
## age_group3 1.70395 1.78365 0.955 0.33996
## age_group4 3.69486 1.96662 1.879 0.06096 .
## age_group5 2.56917 2.27643 1.129 0.25971
## age_group6 8.77580 3.09462 2.836 0.00479 **
## age_group7 1.52274 5.22874 0.291 0.77102
## marital2 0.16659 1.28107 0.130 0.89659
## marital3 -3.07091 5.42792 -0.566 0.57185
## marital4 1.56446 2.44171 0.641 0.52205
## marital5 5.75045 6.49488 0.885 0.37645
## smoking2 1.13926 1.47527 0.772 0.44040
## smoking3 -0.89078 1.55262 -0.574 0.56646
## smoking4 2.24465 1.77194 1.267 0.20593
## smoking5 3.04754 3.34777 0.910 0.36317
## smoking6 -2.36181 4.18504 -0.564 0.57282
## smoking7 6.12418 6.93476 0.883 0.37767
## fivfruitveg2 -1.17530 0.89490 -1.313 0.18978
## shielded2 -1.07324 1.56228 -0.687 0.49248
## week_soc_distancing1 -7.97089 6.35601 -1.254 0.21051
## week_soc_distancing2 3.88815 4.14216 0.939 0.34843
## week_soc_distancing3 -0.53104 3.81225 -0.139 0.88928
## week_soc_distancing4 0.64570 3.54943 0.182 0.85573
## week_soc_distancing5 -1.24050 3.51237 -0.353 0.72413
## week_soc_distancing6 -0.20768 3.63069 -0.057 0.95441
## week_soc_distancing7 3.13844 3.68992 0.851 0.39550
## athlete2 -2.64021 1.18891 -2.221 0.02690 *
## AIMS_TOTAL 0.03081 0.43484 0.071 0.94354
## HADS_OVERALL -0.73496 0.08934 -8.227 2.37e-15 ***
## RES_TOTAL 0.35972 0.11302 3.183 0.00157 **
## LONE_TOTAL -2.37544 0.31793 -7.472 4.55e-13 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.019 on 425 degrees of freedom
## (296 observations deleted due to missingness)
## Multiple R-squared: 0.5926, Adjusted R-squared: 0.5629
## F-statistic: 19.94 on 31 and 425 DF, p-value: < 2.2e-16model_step3 <- lm(MHC_SF_OVERALL ~ gender + age_group +
fivfruitveg + shielded + hour_sleep +
athlete + AIMS_TOTAL + RES_TOTAL + LONE_TOTAL + athlete, data = data) #HADS_OVERALL
summary(model_step3) #<<<<<<##
## Call:
## lm(formula = MHC_SF_OVERALL ~ gender + age_group + fivfruitveg +
## shielded + hour_sleep + athlete + AIMS_TOTAL + RES_TOTAL +
## LONE_TOTAL + athlete, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -25.944 -6.619 0.637 6.939 36.208
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 31.3619 5.4507 5.754 0.0000000163299545 ***
## gender2 1.6328 0.9691 1.685 0.09274 .
## age_group2 1.0628 1.5857 0.670 0.50303
## age_group3 0.9450 1.6538 0.571 0.56800
## age_group4 3.4955 1.7497 1.998 0.04635 *
## age_group5 3.3515 2.1177 1.583 0.11423
## age_group6 11.4471 3.0305 3.777 0.00018 ***
## age_group7 5.0592 4.7406 1.067 0.28646
## fivfruitveg2 -1.7103 0.9542 -1.792 0.07374 .
## shielded2 -0.5426 1.6472 -0.329 0.74202
## hour_sleep 0.6645 0.4714 1.410 0.15936
## athlete2 -2.9128 1.2553 -2.320 0.02077 *
## AIMS_TOTAL -0.1495 0.4524 -0.330 0.74121
## RES_TOTAL 0.8153 0.1059 7.701 0.0000000000000892 ***
## LONE_TOTAL -3.6388 0.2907 -12.516 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.773 on 442 degrees of freedom
## (296 observations deleted due to missingness)
## Multiple R-squared: 0.5025, Adjusted R-squared: 0.4867
## F-statistic: 31.89 on 14 and 442 DF, p-value: < 2.2e-16par(mfrow = c(2, 2))
plot(model_step3)
# Collinearity
library(corrplot)## corrplot 0.84 loadedlibrary(RColorBrewer)
cor_tbl = data %>% select(-MHC_SF_OVERALL) %>%
mutate_each(as.numeric) %>% na.omit() %>% cor()## Warning: `mutate_each_()` is deprecated as of dplyr 0.7.0.
## Please use `across()` instead.
## This warning is displayed once every 8 hours.
## Call `lifecycle::last_warnings()` to see where this warning was generated.corrplot(cor_tbl, type="upper", order="hclust", method="color")
library(corrplot)
library(RColorBrewer)
cor_tbl = data %>% select(-MHC_SF_OVERALL) %>%
mutate_each(as.numeric) %>% na.omit() %>% cor()
corrplot(cor_tbl, type="upper", order="hclust", method="color",
col=brewer.pal(n=8, name="RdYlBu"))
Final Model?
model_step4 <- lm(MHC_SF_OVERALL ~ gender + age_group + fivfruitveg + shielded +
athlete + AIMS_TOTAL + RES_TOTAL + LONE_TOTAL + athlete, data = data)
summary(model_step4)##
## Call:
## lm(formula = MHC_SF_OVERALL ~ gender + age_group + fivfruitveg +
## shielded + athlete + AIMS_TOTAL + RES_TOTAL + LONE_TOTAL +
## athlete, data = data)
##
## Residuals:
## Min 1Q Median 3Q Max
## -25.826 -6.630 0.657 6.916 36.057
##
## Coefficients:
## Estimate Std. Error t value Pr(>|t|)
## (Intercept) 36.1532 4.2658 8.475 3.51e-16 ***
## gender2 1.7718 0.9652 1.836 0.067075 .
## age_group2 0.9342 1.5848 0.590 0.555823
## age_group3 0.6923 1.6459 0.421 0.674229
## age_group4 3.0606 1.7242 1.775 0.076562 .
## age_group5 2.9433 2.1002 1.401 0.161772
## age_group6 11.1693 3.0275 3.689 0.000253 ***
## age_group7 4.8023 4.7424 1.013 0.311789
## fivfruitveg2 -1.7840 0.9538 -1.870 0.062083 .
## shielded2 -0.6186 1.6481 -0.375 0.707601
## athlete2 -2.9981 1.2552 -2.388 0.017337 *
## AIMS_TOTAL -0.1182 0.4523 -0.261 0.793988
## RES_TOTAL 0.8303 0.1055 7.874 2.67e-14 ***
## LONE_TOTAL -3.6993 0.2879 -12.850 < 2e-16 ***
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## Residual standard error: 9.784 on 443 degrees of freedom
## (296 observations deleted due to missingness)
## Multiple R-squared: 0.5002, Adjusted R-squared: 0.4856
## F-statistic: 34.11 on 13 and 443 DF, p-value: < 2.2e-16